SYLVA Labs — enterprise AI governance. See, assess and prove governance across every AI system you run. — Request a demo
AI Governance

Prove your AI is governed.
Not just claimed — evidenced.

AI Pulse is the evidence layer beneath any framework. It discovers every AI system you run — including shadow AI — assesses risk, records ownership and approvals in a tamper-evident ledger, and produces audit-ready evidence you can hand to a board or a regulator. Read-only, deployed in your own tenant.

The Governance Loop

Discover → Assess → Govern → Prove

Governance is not a document you file once. It is a continuous loop: know what you run, judge how risky it is, put owners and controls around it, and keep the evidence current. AI Pulse runs the loop against live cloud signals so the record never goes stale.

01
Discover
Automatically find every AI agent, model, and endpoint across your cloud estate — including shadow AI no one registered. Each system gets an owner, a business unit, and a place in the inventory.
02
Assess
Assign a risk tier to each agent, capture DPIAs and FRIAs where they apply, and record risks, tolerances, and accepted exceptions in a single register. Higher risk pulls tighter controls.
03
Govern
Attach the rules: named owners, maker-checker approvals, and a governance posture per system. Every material decision is written to a tamper-evident ledger — who decided what, and when.
04
Prove
Map controls to the frameworks that apply, see coverage and gaps at a glance, and export audit-ready evidence for boards and regulators — with full provenance on every metric.
Three Interlocking Areas

Governance, Risk and Compliance —
explained plainly

People use "GRC" as one word, but they answer three different questions. AI Pulse keeps them distinct so each has a clear owner, and connects them so evidence flows from one to the next.

Governance — the rules and who owns them
The decision layer. Each AI system carries a governance posture, named owners, and maker-checker approvals so no one ships a high-risk agent alone. Every material decision is written to a tamper-evident ledger — an unbroken record of who approved what, and when.
Risk — the threat and your tolerance
The judgement layer. A risk tier per agent, DPIAs and FRIAs where they apply, and a risk register that tracks each risk, its owner, its tolerance, and any formally accepted exception. Key risk indicators (KRIs) surface when a system drifts past the line you set.
Compliance — the audit
The evidence layer. Controls, coverage, and gaps mapped to the frameworks you have enabled, backed by collected evidence and signed attestations. When an auditor asks "show me", the answer is a coverage view and an export — not weeks of screenshots.
How the three connect
A discovered agent is tiered in Risk, which decides how tight its Governance controls must be.
Governance approvals and ledger entries become the Compliance evidence an auditor accepts.
A gap found in Compliance opens a risk in the register — and the loop continues.
Frameworks

Map a control once,
report to many frameworks

Most AI-governance obligations overlap. AI Pulse maps each control to a common backbone, so a single piece of evidence satisfies the matching clause in every framework you have enabled — no duplicate work per regulator.

Microsoft Responsible AI
Vendor — default backbone
Mapped
ASEAN Guide on AI Governance & Ethics
ASEAN — regional
Mapped
IMDA Model AI Governance Framework
Singapore — incl. Agentic-AI 2026 edition
Mapped
MAS Technology Risk Management
Singapore — financial
Mapped
PDPA
Singapore — data protection
Mapped
EU AI Act
European Union
Mapped
ISO/IEC 42001
International
Mapped
NIST AI RMF
United States
Mapped
The regulators are converging too
You are not the only one mapping across frameworks — the standards bodies do it themselves. NIST publishes crosswalks from the AI RMF to the OECD AI Principles and ISO/IEC standards; IMDA and the ASEAN Guide draw on the same governance principles. AI Pulse rides that convergence: map to the common backbone once, and coverage propagates outward.
Enable only what applies
Turn on the frameworks relevant to your organisation and region. A Singapore bank enables MAS TRM, PDPA and the IMDA framework; a European operator enables the EU AI Act. Each enabled framework recomputes its own coverage from the shared control mapping.
A backbone, not another framework
AI Pulse does not ask you to adopt a new standard. It sits beneath the framework you already answer to and supplies the evidence — whichever framework that is.
The Honesty Engine

Every number carries its provenance.
Missing data shows a dash — never a fake pass.

A governance record is only useful if you can trust it. AI Pulse labels every metric with where it came from, so you always know whether you are looking at a fact, a calculation, or an input — and an unconnected source never quietly turns green.

Live
Read straight from a live cloud API — the resource, its configuration, its telemetry. The strongest form of evidence, current as of the last read.
Derived
Calculated from live signals — a score, a rollup, a ratio. The inputs are traceable, so you can see exactly how the number was reached.
Assumption
A value you supplied — a risk tolerance, an attestation, a configuration input. Labelled as human judgement, not machine fact, so it is never mistaken for measured data.
Not Assessed
The source is not connected or the check has not run, so the value shows an honest "—". AI Pulse never invents a number to fill a gap or paint a fabricated pass.
Why this matters for governance
A dashboard that always looks green is worse than no dashboard — it manufactures false assurance. By showing a dash where evidence is genuinely absent, AI Pulse keeps the board's view honest and gives auditors a record they can rely on. The gaps are the point: they tell you exactly what to connect or assess next.
Get Started

See governance evidence
from your own AI estate.

Request a guided demo. We will walk through the Discover → Assess → Govern → Prove loop against a live environment and show you what audit-ready evidence looks like — with every number labelled for provenance.

Request a demo Contact Us
Read-only • Deployed in your tenant • Evidence with provenance